Our PhD and MS level biostatisticians are highly trained in a range of statistical and analytic methods, including:
- Longitudinal data analysis
- ANOVA, regression, logistic regression
- Bayesian data analyses
- Sample size and power estimation
- Statistical genomics
- Survival analyses
- Principal component and factor analysis
- Path modeling
- Structural equation modeling
- Cluster analysis
- Complex survey data analysis
- Statistical simulations and graphics
- Profile analysis
- Gene expression data analysis
- Mixed effects models
- Generalized Estimating Equations (GEE)
- Propensity Score Matching (PSM)
- Evaluation of medical tests for classification and prediction
- Estimation of median lethal doses (LD50)/quantal dose-response curves
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Biostatisticians & Epidemiologists
Xinhua Yu, MD, PhD Associate Professor of Epidemiology, University of Memphis Xinhua Yu, MD, PhD, MStat, is an Assistant Professor of Epidemiology at the School of Public Health, University of Memphis. He earned a medical degree in preventive medicine from Shanghai Medical University (now College of Medicine at Fudan University) in Shanghai, China, and a PhD in epidemiology and MStat in statistics from the University of Minnesota at Twin Cities campus. Dr. Yu has extensive experience in cardiovascular disease epidemiology, obesity, and physical activity. His recent research interests are clinical epidemiology especially cancer epidemiology.
Mehmet Kocak, PhD Associate Professor of Biostatistics, Preventive Medicine Mehmet earned his M.Sc. degree in applied statistics from Michigan State University and a Ph.D. in statistics from the University of Memphis. He has been a study biostatistician for numerous Phase-I and Phase-II clinical trials conducted by St. Jude Children’s Research Hospital from 2002-2011 and by Pediatric Brain Tumor Consortium (PBTC) from 2002-present, and for clinical and observational studies conducted by University of Tennessee Health Science Center (UTHSC) since 2011. His areas of research have been time-course gene expression data analysis, meta-analysis of p-values, Phase-I clinical trial design, Survival analysis, and categorical data analysis. He is an expert in the SAS programming language as well as SAS/Graph.